How Predictable is Technological Progress?
How Predictable is Technological Progress?
复制标题
技术进步的可预测性如何？
DOI：
10.2139/ssrn.2566810
复制
发表时间：
2015
期刊：
影响因子：
--
通讯作者：
F. Lafond
中科院分区：
文献类型：
--
作者：
J. Farmer;F. Lafond
摘要最近，人们已经清楚地看到，许多技术遵循广义版本的摩尔定律，即成本往往以指数级下降，在不同的速度取决于技术。在这里，我们制定摩尔定律作为一个相关的几何随机游走漂移，并将其应用于历史数据的53项技术。我们推导出一个封闭形式的表达式近似的预测误差的分布作为时间的函数。基于后投实验，我们表明，这是很好的工作，使它能够崩溃的预测误差为许多不同的技术在不同的时间范围内到同一个普遍的分布。这是有价值的，因为它使我们能够对任何给定的技术进行预测，并清楚地了解预测的质量。作为一个实际的演示，我们在不同的时间范围内的太阳能光伏组件的分布预测，并显示我们的方法可以用来估计的概率，一个给定的技术将优于另一种技术在未来的一个给定的点。
Abstract Recently it has become clear that many technologies follow a generalized version of Moore's law, i.e. costs tend to drop exponentially, at different rates that depend on the technology. Here we formulate Moore's law as a correlated geometric random walk with drift, and apply it to historical data on 53 technologies. We derive a closed form expression approximating the distribution of forecast errors as a function of time. Based on hind-casting experiments we show that this works well, making it possible to collapse the forecast errors for many different technologies at different time horizons onto the same universal distribution. This is valuable because it allows us to make forecasts for any given technology with a clear understanding of the quality of the forecasts. As a practical demonstration we make distributional forecasts at different time horizons for solar photovoltaic modules, and show how our method can be used to estimate the probability that a given technology will outperform another technology at a given point in the future.